This invention relates in general to wireless communication networks and, more particularly, to a method and apparatus for modeling a smart antenna in a network planning tool for a wireless communication network.
During the last several years, wireless telephones have enjoyed an progressively increasing popularity among the general population in many countries. In order for a wireless telephone to operate, it must use radio signals to communicate with a wireless network which includes a number of spaced base stations, each of which has multiple antennas supported thereon. The entity that operates the wireless network is commonly referred to as a service provider. In the United States, each service provider is allocated a certain number of frequencies by the government. The service provider then allocates these assigned frequencies among the base stations of that service provider, in a repeating pattern. Each frequency can support only a limited number of telephone calls.
As the popularity of wireless telephony increases, there is progressively increasing pressure on each service provider to increase the call capacity of its wireless network. An increase in the number of available frequencies would increase the capacity, but this is not an option, because of governmental regulation. Accordingly, the service provider must add more base stations and antennas, and/or adjust the pattern of frequency allocation to have a higher density. Both of these techniques have the effect of decreasing the effective distance between base stations which use identical subsets of the allocated frequency set. This in turn increases the potential for interference within the system.
As one example, a wireless telephone attempting to receive signals from a nearby base station may also receive interfering signals from a remote base station operating on the same frequency, thereby causing the person using the telephone to simultaneously hear two conversations. As another example, a base station attempting to communicate with a nearby telephone may also receive signals from a more remote telephone attempting to communicate on the same frequency with a different base station, with the result that two telephone conversations become merged at the base station.
Techniques have been developed to minimize these potential interference problems, while still ensuring telephone calls of good quality. These techniques include adjusting the fixed transmit pattern of a standard antenna, adjusting the transmit power for an antenna, adjusting the height and downward angle of an antenna at a base station, and xe2x80x9cclockingxe2x80x9d the orientation of an antenna a few degrees about a vertical axis at the base station. More recently, these techniques have also included the use of base stations of reduced power, commonly known as micro cells or pico cells. While these techniques have been generally adequate to resolve most problems in the past, existing wireless networks are reaching the limit to which these techniques can reduce or eliminate interference, particularly in urban areas where base stations are relatively closely spaced.
One additional technique, which is a relatively recent development that has not yet been widely used, involves replacing a standard antenna with a more sophisticated type of antenna which is commonly known as a xe2x80x9csmartxe2x80x9d antenna. One type of existing smart antenna is commonly referred to as a switched-beam antenna, and another type of existing smart antenna is commonly referred to as an adaptive beam-forming antenna. Smart antennas have a degree of local intelligence in their operation, which effectively makes them variable pattern antennas rather than fixed pattern antennas, and which allows to them to effectively provide a form of spatial filtering.
Network planners use a type of software program known as a network planning tool (NPT) in order to model a network and the antennas in it, and in order to analyze possible problems such as potential interference. However, existing NPTs do not currently support the use of smart antennas, thus making it difficult or impossible for most network planners to easily integrate a smart antenna into an existing or new network design. One reason for this is that existing NPTs use relatively simple models for standard fixed pattern antennas, and it has been thought that smart antennas require much more sophisticated modeling techniques that cannot be easily integrated into a NPT. In this regard, some attempts have been made to model the operation of the variable patterns of smart antennas, but these attempts involved very sophisticated and complex techniques such as Monte Carlo simulation. As a practical matter, these efforts have basically been limited to academic laboratories and papers, rather than real-world applications, because of the complexity and time-consuming nature of techniques such as Monte Carlo simulation. That is, even if such techniques may work on a theoretical level, the time and complexity involved to carry out the associated calculations make these techniques impractical for NPTs that need to operate on a xe2x80x9creal-timexe2x80x9d basis. In other words, NPT programs using these techniques would run so slowly that they would not be very practical.
Nevertheless, the progressively increasing pressure to provide increased call capacity in existing wireless networks will create increasing pressure for the use of smart antennas in these networks. Consequently, network planners will have a progressively increasing need for NPTs that are capable of modeling smart antennas on an accurate but efficient basis.
From the foregoing, it may be appreciated that a need has arisen for a method and apparatus for modeling smart antennas in the context of wireless communication networks, in a manner which is accurate, simple and efficient.
According to one form of the present invention, this need is addressed by providing a method and apparatus that model a smart antenna which has a directional operating region and which is operative with respect to a frequency group that includes a plurality of frequencies which are different. The modeling involves: representing a transmit pattern of the smart antenna with a plurality of beams that each correspond to a respective different portion of the operating region; and assigning the frequencies of the group approximately randomly among the plurality of beams, each frequency of the frequency group being assigned to one of the beams.
According to a different form of the present invention, the need is met by providing a method and apparatus that model a wireless network which has a plurality of cells that each include at least two cell sections, and which has an antenna serving a first of the cell sections and capable of receiving signals transmitted at a selected frequency. The modeling involves: determining a first power level representing an effective power level as to the antenna for a first signal transmitted at the selected frequency by a hypothetical first mobile transmitter disposed within the first cell section; determining a second power level representing an effective power level as to the antenna for a second signal transmitted at the selected frequency by a hypothetical second mobile transmitter disposed within a second of the cell sections different from the first cell section; and evaluating whether a predetermined value is greater than a difference between the first and second power levels.